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This paper presents a multi-agent structure and optimization algorithm to enhance energy utilization in a flexible jobshop environment under Time-of-Use (TOU) electricity pricing, in the presence of system changes. The proposed control structure based on multi-agent systems (MAS) takes into account re-scheduling in the workshop under TOU pricing. A multi-objective rescheduling model was developed to minimize due dates, makespan, total power consumption, and energy consumption costs. An improved genetic algorithm (GA) was designed to solve this model by converting the multi-objective into a single objective by optimizing each objective individually and combining the results. Simulation results demonstrate the effectiveness of the proposed algorithm and the application of the MAS structure.

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